In this project, images taken from the Sentinel-2 satellite provided by ESA were used. First, after cleaning the data with various preprocessing techniques, a classification was made using many traditional machine learning algorithms. Second, each machine learning algorithm's confusion matrices, accuracy rates, and computation times are compared. As a result of these comparisons, land cover classification was made with the best-performing algorithm. The academic paper of the project was also written.
